Design and implementation of personal loan processing systems using AI technique - Lee, Jason Chia Shen (2024)
This project focuses on the design and implementation of personal loan processing system using artificial intelligence technique. With the issue of manual and tedious tasks in traditional personal loan processing operations, many banking and financial institutions have not seen substantial increase in their productivity. As for that, this project has proposed a personal loan system to automate the manual loan processes. The borrower can get their creditworthiness and eligibility for a loan checked in an accurate manner and in a very short time. This project integrates a gradient boosting model (XGBoost) and SHAP (Shapley Additive exPlanations) values to accurately predict the creditworthiness of the borrower in the context of loan approval. Furthermore, to tackle the issue of inadequate credit history, the digital footprints of the borrower will also be used to compute their eligibility for a loan. The proposed personal loan system is light weight to be deployed in real world conditions where time and performance matter. This system will comply to all the ethical standards and regulations to give the borrower a peace of mind when using the system. The system will be transparent enough to be used in real banking and financial organizations.